We use CityScapes [1]} as our training (2975 images) and validation (500 images) datasets. We use FCN [2]}, PSANet [3]}, DeepLabV3 [4]} and DeepLabV3+ [5]} as our baseline models. The input sizes are set as \(769\times 769\) . All models are trained for \(40K\)  iterations. More details can be referred to the Github repository mmsegmention\(\endcsname \)https://github.com/open-mmlab/mmsegmentation.git
. As shown in Table REF , ADC can bring consistent improvements to different Semantic Scene Parsing models. For FCN, ADC even improves the mIOU by \(4.27\) .
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